Triple

T3405287
Position Surface form Disambiguated ID Type / Status
Subject Ferenc Münnich E71756 entity
Predicate placeOfBirth P1 FINISHED
Object Seregélyes E236811 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Seregélyes | Statement: [Ferenc Münnich, placeOfBirth, Seregélyes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seregélyes
Context triple: [Ferenc Münnich, placeOfBirth, Seregélyes]
  • A. Mátraháza
    Mátraháza is a small mountain resort village in northern Hungary, known for its scenic location in the Mátra range and its hiking and wellness tourism.
  • B. Somlyó
    Somlyó is a historical locality in the Kingdom of Hungary, best known as the birthplace of Stephen Báthory, who became King of Poland and Grand Duke of Lithuania in the 16th century.
  • C. Bicske chosen
    Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
  • D. Tiszaújváros
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • E. Keszthely
    Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad85aac4808190a092c9cc8911f584 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb8eaa41c819095a4d51aec074649 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bd8c0ec8190bd44d33fc031c845 completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:15 p.m.